{
    "action": "tool_call",
    "reasoning": "I've seen the deal stage distribution and temporal patterns, but to identify the most surprising finding, I need to explore potential anomalies or counterintuitive patterns. One area that stands out is the product performance - GTK 500 has only 40 total deals (15+15+10) compared to 1,866+ for other products, yet generated $400k in won value. Let me check if this represents an unusually high value-per-deal that would be counterintuitive.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT p.product, p.sales_price, COUNT(sp.opportunity_id) as total_deals, SUM(CASE WHEN sp.deal_stage = 'Won' THEN 1 ELSE 0 END) as won_deals, SUM(CASE WHEN sp.deal_stage = 'Won' THEN sp.close_value ELSE 0 END) as total_won_value, ROUND(SUM(CASE WHEN sp.deal_stage = 'Won' THEN sp.close_value ELSE 0 END) * 1.0 / NULLIF(SUM(CASE WHEN sp.deal_stage = 'Won' THEN 1 ELSE 0 END), 0), 2) as avg_deal_value, ROUND(p.sales_price, 2) as list_price FROM raw.products p LEFT JOIN raw.sales_pipeline sp ON p.product = sp.product GROUP BY p.product, p.sales_price ORDER BY avg_deal_value DESC",
        "purpose": "Compare actual average deal values against product list prices to identify pricing anomalies or discounting patterns",
        "source": "raw"
    }
}